得克萨斯大学奥斯汀分校 AI for Medicine 招博士生和博士后
3410
About Lab (xiazlab.org)
The Xia lab will join the Biomedical Engineering Department at the UT Austin in August 2026, supported by the Texas CPRIT Scholar Recruitment award. In our phenotype-centered computational biology laboratory, we aim to develop machine learning-based tools for novel biological and clinical discoveries. These discoveries are further validated experimentally and translated into clinical applications through collaborations with biologists and clinicians.We focus on tissue microenvironments, virtual cells, AI agents, and predictive precision medicine, leveraging machine learning and artificial intelligence techniques at the Texas Advanced Computational Center at UT Austin to analyze multimodal datasets, including genomics, proteomics, and imaging at single-cell resolution. Our research is dedicated to addressing human diseases, particularly cancer and neurodegenerative diseases.
Our work is funded by the NIH, DoD, and CPRIT. The lab is affiliated with the Oden Institute and Dell Medical School, with access to clinical data through collaborations with medical centers across the U.S., including UT MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, UT Southwestern Medical Center, Fred Hutchinson Cancer Research Center and others.The PI is committed to helping you develop a unique career path in artificial intelligence for biomedicine and to publishing papers in high-impact journals. The trainee will work with one of the directions: digital twin of the tumor microenvironment, liquid biopsies, and AI Agents for biomedical discoveries.
Research projects：
1.Machine learning/deep learning algorithms for single-cell data analysis (Nature Biotechnology 2018, 2022; Nature Machine Intelligence 2023; Cell Genomics 2025; Cancer Discovery 2026)
2.Cancer treatment resistance（Clinical Cancer Research, 2020, 2021; PNAS, 2020).
3.Cancer Immunotherapy (Nature, 2022)
4.Predictive medicine (Nature Communications 2021, 2022)
The postdoc’s salary will be competitive and commensurate with experience. The PhD students will be recruited through the Biomedical Engineering PhD program.
Qualification Requirements
The applicants must have degrees in Computer Science, Mathematics, Computational Biology, Statistics, Genetics, Bioinformatics, Biostatistics, or related fields.
First-author publications in peer-reviewed scientific journals and conferences.
Track record in developing AI/ML models, particularly for biomedical applications, including medical imaging, single-cell analysis, spatial analysis or multi-omics integrations.
Strong self-motivation for research.
If you are interested, please send a cover letter, your CV, along with the contact information of two referees to 1point3acres.com.
The Xia lab will join the Biomedical Engineering Department at the UT Austin in August 2026, supported by the Texas CPRIT Scholar Recruitment award. In our phenotype-centered computational biology laboratory, we aim to develop machine learning-based tools for novel biological and clinical discoveries. These discoveries are further validated experimentally and translated into clinical applications through collaborations with biologists and clinicians.We focus on tissue microenvironments, virtual cells, AI agents, and predictive precision medicine, leveraging machine learning and artificial intelligence techniques at the Texas Advanced Computational Center at UT Austin to analyze multimodal datasets, including genomics, proteomics, and imaging at single-cell resolution. Our research is dedicated to addressing human diseases, particularly cancer and neurodegenerative diseases.
Our work is funded by the NIH, DoD, and CPRIT. The lab is affiliated with the Oden Institute and Dell Medical School, with access to clinical data through collaborations with medical centers across the U.S., including UT MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, UT Southwestern Medical Center, Fred Hutchinson Cancer Research Center and others.The PI is committed to helping you develop a unique career path in artificial intelligence for biomedicine and to publishing papers in high-impact journals. The trainee will work with one of the directions: digital twin of the tumor microenvironment, liquid biopsies, and AI Agents for biomedical discoveries.
Research projects：
1.Machine learning/deep learning algorithms for single-cell data analysis (Nature Biotechnology 2018, 2022; Nature Machine Intelligence 2023; Cell Genomics 2025; Cancer Discovery 2026)
2.Cancer treatment resistance（Clinical Cancer Research, 2020, 2021; PNAS, 2020).
3.Cancer Immunotherapy (Nature, 2022)
4.Predictive medicine (Nature Communications 2021, 2022)
The postdoc’s salary will be competitive and commensurate with experience. The PhD students will be recruited through the Biomedical Engineering PhD program.
Qualification Requirements
The applicants must have degrees in Computer Science, Mathematics, Computational Biology, Statistics, Genetics, Bioinformatics, Biostatistics, or related fields.
First-author publications in peer-reviewed scientific journals and conferences.
Track record in developing AI/ML models, particularly for biomedical applications, including medical imaging, single-cell analysis, spatial analysis or multi-omics integrations.
Strong self-motivation for research.
If you are interested, please send a cover letter, your CV, along with the contact information of two referees to 1point3acres.com.
